Text Classification
Transformers
TensorBoard
Safetensors
English
bloom
aging
social-media
reddit
generationing
Eval Results (legacy)
Instructions to use ernchern/personal_info_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ernchern/personal_info_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ernchern/personal_info_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ernchern/personal_info_classification") model = AutoModelForSequenceClassification.from_pretrained("ernchern/personal_info_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57ed524c2ee3f13f243d98f5d1273b9fd0c3f82b1e0141d6011515406fcdde0d
- Size of remote file:
- 14.5 MB
- SHA256:
- 85b00d7db4df5df2e3f01cacc3feda246002a672f3356eec7f4b04a22eb0dfbe
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